Abstract

To ensure that a regular milled surface texture provides good bonding without residual distress, a new specification of milling surface assessment has been established for quantitatively evaluating the milled surface quality. This research explores the possibility of using three-dimensional (3D) laser scanning technology to develop an algorithm to obtain a milled surface model that can measure evaluating indicators, milling depth and texture depth, and identify poorly milled areas. A case study was conducted by using a laser scanning vehicular system to collect 3D continuous pavement transverse profiles data in a 500 m long segment of Highway S107. The results show that the proposed method is very promising and can measure the milling depth and texture depth to effectively and quantitatively differentiate between good- (milling depth between 47 mm and 53 mm and texture depth exceeding 2 mm) and poor-quality work. Moreover, the poorly milled areas such as those with residual distress and unmilled areas that will lead to premature failure can also be identified using the proposed method. The proposed method can effectively support remilling work and ensure the quality of the overlay pavement.